A Genetic Algorithm for Feeding Trajectory Optimisation of Fed-batch Fermentation Processes

In this work a genetic algorithm is proposed with the purpose of the feeding trajectory optimization during a fed-batch fermentation of E. coli. The feed rate profiles are evaluated based on a number of objective functions. Optimization results obtained for different feeding trajectories demonstrate that the genetic algorithm works well and shows good computational performance. Developed optimal feed profiles meet the defined criteria. The ration of the substrate concentration and the difference between actual cell concentration and theoretical maximum cell concentration is defined as the most appropriate objective function. In this case the final cell concentration of 43 g·l-1 and final product concentration of 125 g·l-1 are achieved and there is not significant excess of substrate

Application of Topological Operators over Data from InterCriteria Analysis

In this paper, two topological operators T and U over intuitionistic fuzzy sets are considered and applied. As a case study a parameter identification problem of E. coli fed-batch cultivation process model using genetic algorithms is investigated. A new result regarding T and U is established. The results obtained by the application of the topological operators over data processed by InterCriteria Analysis are discussed

Optimal Feeding Trajectories Design for E. coli Fed-batch Fermentations

In this paper optimal control algorithms for two E. coli fed-batch fermentations are developed. Fed-batch fermentation processes of E. coli strain MC4110 and E. coli strain BL21(DE3)pPhyt109 are considered. Simple material balance models are used to describe the E. coli fermentation processes. The optimal feed rate control of a primary metabolite process is studied and a biomass production is used as an example. The optimization of the considered fed-batch fermentation processes is done using the calculus of variations to determine the optimal feed rate profiles. The problem is formulated as a free final time problem where the control objective is to maximize biomass at the end of the process. The obtained optimal feed rate profiles consist of sequences of maximum and minimum feed rates. The resulting profiles are used for optimization of the E. coli fed-batch fermentations. Presented simulations show a good efficiency of the developed optimal feed rate profiles

Determination of the microplastic particle release by tea bags during brewing

The presence of microscopic particles of plastic (MP) in food is currently an urgent problem in the modern food industry and one of the main issues of food safety. However, there are no clear methods for the determination of such particles, nor methods for cleaning food products from them. In the present work, for the first time, the method of Dynamic Laser Light Scattering (DLS) was used to determine the plastic nanoparticles from tea bags when they were boiled in boiling water. It has been established that some of the studied samples of sachets release a huge amount of such nanoparticles into water. Moreover, hundreds of millions of nanoparticlesare released per one microscopic particle

Noise Reduction of Measurement Data using Linear Digital Filters

In this paper Butterworth, Chebyshev (Type I and II) and Elliptic digital filters are designed for signal noise reduction. On-line data measurements of substrate concentration from E. coli fed-batch cultivation process are used. Application of the designed filters leads to a successful noise reduction of on-line glucose measurements. The digital filters presented here are simple, easy to implement and effective - the used filters allow for a smart compromise between signal information and noise corruption

Modelling of a Fed-Batch Culture Applying Simulated Annealing

In this paper the metaheuristic Simulated Annealing (SA) is applied for parameter identification of non-linear model of cultivation process. SA algorithm is a stochastic relaxation technique, using the Metropolis algorithm based on the Boltzmann distribution in statistical mechanics, for solving nonconvex optimization problems. A real E. coli MC4110 fed-batch cultivation process is considered. The mathematical model is presented by a system of five ordinary differential equations, describing the regarded cultivation process variables - biomass, substrate, acetate, dissolved oxygen and bioreactor volume increasing. The obtained criteria values show that the developed model is adequate and has a high degree of accuracy. The presented results are a confirmation of successful application of the SA algorithm and of the choice of SA algorithm parameters

Single and Multiple variables control using Tree Physiology Optimization

This paper presents the tuning of single-input single-output (SISO), and multiple-input multiple-output (MIMO) control system using Tree Physiology Optimization (TPO). TPO is a metaheuristic optimization algorithm that has a clustered diversification search strategy inspired from plant shoots growth. The clustered diversification is referred as tree branch and leaves. The exploration is amplified from roots growth counterparts. In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). Results shown that TPO is able to find good PID parameters with lesser settling time for SISO and MIMO process. NMS is also able to find good PID parameters for SISO with lesser performance index, however not able to find better solution in MIMO control. PSO converged prematurely in SISO control and has high overshoot for MIMO control optimization

INFLUENCE OF THE “PUSH & FLICK” METHODOLOGY ON THE ACCURACY OF THE INDOOR HOCKEY PENALTY CORNER SHOOTING

The penalty corner (PC) is one of the most important game situations in hockey (both outdoors and indoors), which results in 30 – 40% of all goals. The aim of this paper is to study the influence of the quasi-experimental methodology on the dynamics in the development of indicators characterizing the accuracy of shooting when performing PC in the potentially effective goal zones. Through the application of InterCriteria Analysis (ICrA), the research team sought to establish relationships and directions of dependencies between indicators reflecting the accuracy of zone shooting. Four elite female indoor hockey players from the team of the National Sports Academy in Bulgaria, participants in the European Indoor Hockey Clubs Challenge, were involved in the examination sessions. According to the requirements of the quasi-experimental “Push & Flick” methodology, the duration of the specialized training was set to 16 weeks. Each player performed 4,800 shootings, or approximately 300 shootings each week. Tests were carried out at the beginning (the first week) and at the end (the sixteenth week) of the experiment in order to determine the accuracy of the shooting – push/flick from a penalty corner spot (9 meters, central from the goal line). We used InterCriteria Analysis and Variance Analysis to analyze the results. The results of the study provide valuable information related to the training and specialization of elite hockey players profiled in the execution of a penalty corne